Introduction

In the realm of fantasy literature and cinema, few franchises have captured the imagination quite like Harry Potter. But beyond the spellbinding narratives lies a wealth of data waiting to be explored. Our analysis aims to uncover the hidden patterns and insights within the Harry Potter movie series, using a comprehensive dataset that spans characters, dialogue, spells, and movie statistics.

The central question we seek to answer is: How do the various elements of the Harry Potter universe interact and evolve throughout the series? To address this, we’ll be diving into multiple CSV files, including:

• Chapters.csv: Contains information about movie chapters, including character IDs, chapter names, movie IDs, and chapter numbers within each movie script.
• Characters.csv: Provides detailed information about characters, including their species, gender, Hogwarts house, patronus, and wand properties.
• Dialogue.csv: Contains every line of dialogue from the movie scripts, linked to characters, chapters, and locations.
• Movies.csv: Offers production details for each movie, including title, release year, runtime, budget, and box office performance.
• Places.csv: Lists various locations in the Harry Potter universe, categorized by type.
• Spells.csv: Details the various spells used in the series, including their incantations, effects, and associated light.

By analyzing this rich dataset, we aim to reveal trends in character development, explore the complexity of magic over time, and even draw connections between the fictional world and real-world factors like movie budgets and audience reception. Whether you’re a die-hard fan or a data enthusiast, this analysis promises to shed new light on the intricate tapestry of the wizarding world, all through the lens of data science.

About the Dataset

Data Sources

The datasets used in this analysis come from two main sources (Kaggle):

1. Harry Potter Movies Dataset - Contains detailed movie scripts and dialogue information
2. Harry Potter Dataset - Provides comprehensive character attributes and demographics

Tools

Our analysis uses various R packages to process and visualize the data:

• dplyr - For efficient data manipulation and transformation
• ggplot2 - For creating sophisticated visualizations of character demographics and dialogue patterns
• kableExtra - For creating formatted tables with additional styling options
• knitr - For generating dynamic reports and tables
• RColorBrewer - For consistent and visually appealing color schemes
• stringr - For string manipulation and text processing
• tidyr - For cleaning and restructuring data into tidy format
• tidytext - For text analysis and processing of dialogue
• wordcloud - For visualizing word frequencies in dialogue

Through statistical analysis and data visualization, we explore several key aspects:

1. Demographics and characteristics of different Hogwarts houses
2. Character attribute distributions (blood status, physical traits, magical abilities)
3. Dialogue patterns and language use throughout the series

This analysis will provide fans, researchers, and storytellers with quantitative insights into the intricate world of Harry Potter, revealing patterns that might not be immediately apparent through casual viewing or reading.

## Rows: 61
## Columns: 5
## $ Spell.ID    <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,…
## $ Incantation <chr> "Accio", "Aguamenti", "Alarte Ascendare", "Alohomora", "Ar…
## $ Spell.Name  <chr> "Summoning Charm", "Water-Making Spell", "Launch an object…
## $ Effect      <chr> "Summons an object", "Conjures water", "Rockets target upw…
## $ Light       <chr> "", "Icy Blue", "Red", "Blue", "Blue", "", "Green", "", "B…

## Rows: 74
## Columns: 3
## $ Place.ID       <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, …
## $ Place.Name     <chr> "Flourish & Blotts", "Gringotts Wizarding Bank", "Knock…
## $ Place.Category <chr> "Diagon Alley", "Diagon Alley", "Diagon Alley", "Diagon…

## Rows: 7,444
## Columns: 5
## $ Dialogue.ID  <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
## $ Chapter.ID   <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, …
## $ Place.ID     <int> 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, …
## $ Character.ID <int> 4, 7, 4, 7, 4, 7, 4, 5, 4, 5, 7, 4, 7, 4, 4, 4, 32, 31, 3…
## $ Dialogue     <chr> "I should have known that you would be here...Professor M…

House Dynamics

This analysis explores the characteristics and demographics of different Hogwarts houses and magical schools using the Characters dataset. We examine several key variables including:

• House affiliation (Gryffindor, Slytherin, Ravenclaw, Hufflepuff, Beauxbatons, Durmstrang)
• Gender distribution within houses
• Blood status diversity (Pure-blood, Half-blood, Muggle-born, etc.)
• Physical characteristics (Hair color, Eye color)
• Magical abilities (Patronus forms)

Distribution of Characters Across Hogwarts Houses

The main houses and schools in the Harry Potter universe include:

• Gryffindor: Known for bravery, daring, nerve, and chivalry. Associated with the lion and the colors scarlet and gold.
• Slytherin: Values ambition, cunning, leadership, and resourcefulness. Represented by the serpent with colors green and silver.
• Ravenclaw: Prizes wit, learning, wisdom, and intellect. Symbolized by the eagle with blue and bronze colors.
• Hufflepuff: Emphasizes hard work, dedication, patience, and loyalty. Represented by the badger with yellow and black colors.
• Beauxbatons: A French magical academy known for elegance and refinement.
• Durmstrang: A Northern European institution famous for its emphasis on martial magic and physical prowess.

Gender Distribution

Blood Status Diversity

In the Harry Potter universe, there are several distinct blood statuses:

• Pure-Blood: Wizards and witches from families with exclusively magical heritage for many generations
• Half-Blood: Those with both magical and non-magical ancestry in their recent family history
• Muggle-Born: Magical individuals born to non-magical (Muggle) parents
• Half-Giant: Individuals with one giant parent and one human parent
• Quarter-Veela: Those with one grandparent who was a Veela (magical beings known for their beauty)
• Goblin: Members of the goblin race, known for their exceptional skill with metals and banking
• Part-Goblin: Characters with some goblin ancestry in their family line
• Squib: People born to magical parents but lacking magical abilities themselves
• House-Elf: Magical creatures bound to serve wizarding households and institutions

Physical Characteristics

Patronus Forms

A Patronus is a powerful defensive charm in the Harry Potter universe that manifests as a bright, silvery-white guardian or protector taking the form of an animal. This advanced magic serves primarily as protection against dark creatures like Dementors and Lethifolds.

Each witch or wizard’s Patronus typically takes a unique animal form that reflects their personality.

The incantation “Expecto Patronum” is used to conjure a Patronus, but the spell requires both the incantation and intense focus on a powerful, happy memory to be successful.

• None: Wizards and witches who cannot produce a Patronus charm
• Non-corporeal: A shield of silver mist rather than a distinct animal form

Dialogue Analysis

To analyze dialogue patterns across the Harry Potter movie series, we examined the following datasets:

• Dialogue.csv: Contains character dialogue lines with Character.ID and Chapter.ID
• Characters.csv: Provides character details including House affiliation
• Chapters.csv: Links dialogues to specific movie chapters
• Movies.csv: Contains movie titles and chronological information

Key variables analyzed include:

• Individual dialogue lines and their frequency
• Distribution of dialogue across Houses
• Speaking patterns of main characters (Golden Trio)
• Common words and phrases used throughout the series

Frequently Used Words

Locations with Most Dialogue

These locations serve as essential backdrops for character interactions and plot development throughout the series, each with its own unique atmosphere and significance to the story.

• Diagon Alley: main shopping district for wizards in London, featuring essential magical shops like Ollivanders (wands), Gringotts Bank, and the famous Weasleys’ Wizard Wheezes joke shop.
• Dwellings: Important residences including the Burrow (Weasley family home), 4 Privet Drive (Harry’s childhood home), and 12 Grimmauld Place (Order of the Phoenix headquarters).
• Hogsmeade: The only all-wizard village in Britain, featuring popular establishments like The Three Broomsticks inn, Honeydukes sweet shop, and the supposedly haunted Shrieking Shack.
• Hogwarts: The magical school contains numerous important locations:
  • Common areas: Great Hall, Library, Hospital Wing
  • Educational spaces: Various classrooms for Potions, Charms, and Defense Against the Dark Arts
  • Secret locations: Chamber of Secrets, Room of Requirement
  • Outdoor areas: Quidditch Pitch, Forbidden Forest, Great Lake
• Other Magical Locations: Various magical places including Platform Nine and Three-Quarters (train station), the Ministry of Magic (government headquarters), and the Knight Bus (magical emergency transport).

Representation of Different Houses in Dialogue Across the Movie Series

Golden Trio Dialogue Distribution

The Golden Trio: Harry Potter, Ron Weasley, and Hermione Granger - form the central characters of the series.

Their dialogue distribution across the movies reveals interesting patterns in character development and story focus:

• Harry consistently has the highest number of lines throughout the series, reflecting his role as the protagonist
• Hermione’s dialogue peaks noticeably in the films where she has crucial plot-advancing moments
• Ron’s dialogue distribution shows more variation, with stronger presence in the last film (part 1)

Several key observations from the dialogue analysis:

• There’s a noticeable shift in dialogue distribution during the later films, especially in the Deathly Hallows parts
• Individual character arcs are reflected in their dialogue patterns - for example, Hermione’s increased prominence during academic challenges and Ron’s reduced presence during his temporary departure in Deathly Hallows Part 1

Spell Analysis

To find spell usage by each character and house we utilize a function to search through every line of dialogue searching for occurrences of spell incantations and then record the which character used the spell and what spell they used.

To analyze spell usage throughout the Harry Potter movies we examined the following datasets:

• Dialogue.csv: Contains each line of dialogue and who said it

• Spells.csv: Contains the spell incantations

Key Variables include:

• Individual dialogue lines and the incantations they contain

• Character names

• House names

• Incantations (e.g. Sectum Sempra, Expelliarmus)

Spell Finder Function

The SpellFinder function identifies spell incantations in dialogue by:

• Scanning through lines of dialogue to find exact matches of known spell incantations
• Creating a data frame that pairs each line of dialogue with the spell being cast
• Handling multiple spells that may appear in the same dialogue

The analysis tracks how these spells are used across different characters, chapters, and contexts throughout the series.

SpellFinder <- function(dialogueDF, spellsDF) {
  #Initializes up the matches data frame to hold the 
  #line of dialogue and spell being used in that line of dialogue.
  Matches <- data.frame(
    Dialogue = character(),
    Spell = character()
  )
  #for each spell in the Spells data frame we identify which lines of 
  #dialogue contain that spell and add those lines of dialogue to the MatchingLines vector.
  for (spell in spellsDF$Incantation) {
    MatchingLines <- dialogueDF$Dialogue[str_detect(
      dialogueDF$Dialogue,spell)]
      
#Stores the vector MatchingLines in a temporary data 
#frame and Labels each dialogue with the spell found in them from this iteration of the loop.
    MatchesTemp <- data.frame(
      Dialogue = MatchingLines,
      Spell = rep(spell, length(MatchingLines))
    )
#Once we have a temporary data frame with each of the 
#lines of dialogue and have labeled them by the 
#spell used we can add the dialogues with this 
#iterations spells to a final data frame which will hold 
#all lines of dialogue with a spell from all iterations at the end of the loop
      Matches <- rbind(Matches,MatchesTemp)
      }
  
  return(Matches)
}

Spell Usage by the Golden Trio

Spell Frequency Across Movie Series

Spell Frequency by Character

Spell Frequency by House

Spell Frequency by Gender

Wand Analysis

To analyze wand characteristics and their distribution across the Harry Potter universe, we examined the following datasets:

• Characters.csv: Contains wand details including wood type, core, and length

Key variables analyzed include:

• Wand Length (inches)
• Wand Wood Type (e.g., Holly, Oak, Vine)
• Wand Core Material (e.g., Phoenix feather, Dragon heartstring)
• Character House Affiliation

Distribution of Wands Across Houses

Wand Length Distribution by Wood Type and Core

Analysis Summary

Problem Statement and Key Insights

This analysis explored the Harry Potter universe through multiple datasets examining wand characteristics, spell usage patterns, and characters across houses and throughout the series. The primary goal was to uncover patterns and relationships in magical elements across different demographic groups.

Key findings include:

• Distinct distribution patterns across houses, showing house-specific preferences in magical implements
• Correlation patterns between wand woods, cores, and lengths, suggesting certain combinations are more common than others
• Varied spell usage patterns among the Golden Trio (Harry, Ron, and Hermione), highlighting their different approaches to magic
• Evolution of spell usage throughout the series, demonstrating how magical complexity increases as the story progresses

Implications and Limitations

Implications:

• The analysis reveals systematic patterns in magical practice that align with character backgrounds and affiliations
• Gender differences in spell usage might reflect broader themes about character roles and development in the series

Limitations:

• Data completeness: Some characters in the series have more detailed documentation than others
• Context limitation: The analysis cannot account for application of spells (mention vs incantation)

Fun Data:

• Ron is pretty useless when it comes to magic!(Kinda already knew that)
• Slytherin has the most half-bloods by percentage.(Very weird)
• We don’t see anyone from hufflepuff cast a spell in any of the movies!